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TRUVACE RECORD VERSION
record: TRV-2026-1691
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-17T10:42:26.704595Z
status: published
lens: trace
sector: health
headline: Fully Automated Artificial Intelligence-Based Design Single Tooth-Supported Dental Crowns: A Systematic Review of Efficiency, Fit, and Morphological Accuracy
dek: Abstract Fully automated artificial intelligence (AI)-based dental crown design has recently emerged as an alternative to conventional workflows, including technician-assisted digital design and traditional wax-up techniques. However, the available evidence remains heterogeneous, and no clear consensus exists regarding its performance in terms of time efficiency, fit, and morphological accuracy. We aimed to systematically evaluate whether fully automated AI-based crown design provides comparable or superior outc…
gain_title: Fully automated AI design of single dental crowns consistently reduced working time versus conventional digital or wax-up workflows while keeping marginal gap and internal fit generally within clinically acceptable limits.
problem_title: Evidence does not show AI is systematically superior: morphological accuracy results were mixed, and the studies were heterogeneous and largely in vitro under idealized conditions.
trace_subject: Fully automated AI design of single tooth-supported dental crowns
gain_reading: Fully automated AI design of single dental crowns consistently reduced working time versus conventional digital or wax-up workflows while keeping marginal gap and internal fit generally within clinically acceptable limits.
gain_evidence: Time efficiency was consistently improved in AI-based workflows compared with conventional digital or wax-up techniques. | most values remaining within clinically acceptable thresholds
problem_reading: Evidence does not show AI is systematically superior: morphological accuracy results were mixed, and the studies were heterogeneous and largely in vitro under idealized conditions.
problem_evidence: the current evidence does not support systematic superiority of AI across all evaluated parameters | the predominance of in vitro studies conducted under idealized conditions
quick_read: A systematic review screened 1291 records across four databases and included nine studies comparing fully automated AI crown design with technician-assisted digital design and traditional wax-up methods. Across the studies, AI workflows were faster, and fit measures were generally comparable to conventional digital approaches.

The findings suggest AI could save labor time in prosthetic dentistry without sacrificing acceptable fit, but the picture is incomplete. Morphological accuracy results split between AI and technician-assisted designs, and the authors call for standardized, clinically oriented studies before routine adoption.
limitation: The evidence base is heterogeneous, with inconsistent outcome definitions, varied software and evaluation protocols, and mostly in vitro studies under idealized conditions, so clinical superiority cannot be concluded.
tag: Dual reading
key_points: Nine studies were included from 1291 records, following PRISMA guidelines and a registered protocol. | Four studies had low risk of bias, four moderate, and one clinical study was of good methodological quality. | Marginal gap and internal fit were generally comparable between AI and conventional digital workflows. | Morphological accuracy was heterogeneous, with some studies favoring AI and others technician-assisted workflows. | Inconsistent definitions of outcomes such as accuracy and work time limit comparison across studies.
rundown: The review searched PubMed/MEDLINE, Embase, Web of Science, and Cochrane for studies of single dental crowns designed by fully automated AI systems. It excluded implant-supported or partial crowns, noncomparative simulations unrelated to crown fabrication, and studies lacking a conventional comparator.

Risk of bias was assessed with the QUIN tool for in vitro studies and the Newcastle-Ottawa Scale. Outcomes covered time efficiency, marginal gap, internal fit, and morphological accuracy against technician-assisted digital design and wax-up techniques.

The authors conclude that AI crown design shows promise, especially for reducing working time while keeping fit and morphology comparable to conventional digital workflows. They say further standardized, clinically oriented research is needed to validate routine integration into prosthetic dental practice.
sources:
- peer_reviewed | European Journal of Dentistry | https://doi.org/10.1055/s-0046-1829082 | 2026-10-08
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